Usage

First, install django-aetos:

pip install django-aetos

then, add the app to settings.py:

INSTALLED_APPS = [
    # ... other apps ...
    "django_aetos",
    # ... other apps ...
]

configure aetos in settings.py:

ℹ️ Important: When using django-aetos in a project behind a reverse proxy, include django-xff in your project, so that a request’s REMOTE_ADDR header gets rewritten to the correct client ip.

# on enabled ip allowlist with empty list, requests are denied
AETOS_ENABLE_IP_ALLOWLIST = True
AETOS_IP_ALLOWLIST = ["127.0.0.1"]

# enables authentication via bearer token
# if enabled with empty list, requests are denied
AETOS_ENABLE_AUTH = True
AETOS_AUTH_TOKENLIST = ["ooy9Evuth0zahka"]

and send requests to /metrics to Aetos in your urls.py:

from django.urls import include

urlpatterns = [
    path("", include("django_aetos.urls")),
    # ... your other patterns ...
]

Then, add your own metrics using the @metric_collector decorator. Your signal handler can return multiple metrics, each represented as a dict within a list of generator.

Your src/app/signals.py:

from django_aetos.signals import metric_collector


@metric_collector(category="cheap")
def metric_universes_count(sender, **kwargs):
    yield {
        "name": "universes_count",
        "help": "Total number of universes",
        "type": "counter",
        "value": 1,
    }


@metric_collector(category="expensive")
def metric_complex_calculation(sender, **kwargs):
    yield {
        "name": "complex_metric",
        "help": "An expensive calculation",
        "type": "gauge",
        "value": some_expensive_database_query(),
    }

You can do anything you like here, like make database queries or look at files in the filesystem.

Multiple Metric Endpoints

Metrics are organized by category. You can scrape different categories at different intervals:

• /metrics - Returns ALL metrics (all categories combined)

• /metrics/cheap - Returns only metrics tagged with category=”cheap”

• /metrics/expensive - Returns only metrics tagged with category=”expensive”

This allows you to scrape cheap metrics frequently and expensive metrics less often.

Categories are arbitrary strings - use any names that make sense for your use case (e.g., “fast”, “slow”, “realtime”, “daily”, etc.).

Legacy Pattern

The old signal-based pattern still works for backward compatibility:

from django.dispatch import receiver
from django_aetos.signals import collect_metrics


@receiver(collect_metrics, dispatch_uid='metric_legacy')
def metric_legacy(sender, **kwargs):
    yield {
        "name": "legacy_metric",
        "help": "Using the old pattern",
        "type": "counter",
        "value": 42,
    }

Metrics registered this way appear on /metrics but not on category-specific endpoints.

To make sure your receiver actually connects, add an import to your src/app/apps.py:

from django.apps import AppConfig

class YourAppConfig(AppConfig):
    name = "yourapp"

    def ready(self):
        from . import signals  # NOQA

Dev Setup

python3 -m venv venv
source venv/bin/activate
make setup
make install-dev

Testing

make test

Packaging

git pull
make bump-version part=minor
git push origin main v$(bump-my-version show current_version)

make build
make upload-test

once the package looks good, run make upload.